Web-Based Query Translation for English-Chinese CLIR

Abstract

Dictionary-based translation is a traditional approach in use by cross-language
information retrieval systems. However, significant performance degradation is
often observed when queries contain words that do not appear in the dictionary.
This is called the Out of Vocabulary (OOV) problem. In recent years, Web mining
has been shown to be one of the effective approaches for solving this problem.
However, the questions of how to extract Multiword Lexical Units (MLUs) from
the Web content and how to select the correct translations from the extracted
candidate MLUs are still two difficult problems in Web mining based automated
translation approaches.
Most statistical approaches to MLU extraction rely on statistical information
extracted from huge corpora. In the case of using Web mining techniques for
automated translations, these approaches do not perform well because the size of
the corpus is usually too small and statistical approaches that rely on a large sample
can become unreliable. In this paper, we present a new Chinese term measurement
and a new Chinese MLU extraction process that work well on small corpora. We
also present our approach to the selection of MLUs in a more accurate manner. Our
experiments show marked improvement in translation accuracy over other
commonly used approaches.

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